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Abstract
This paper intends to model time series with the aim of per-form forecast using integer and fractional differencing for agricultural
commodities future’s price. Time series models of the ARMA/ARIMA
type (integer differencing) will be estimated and compared to ARFIMA
type models (fractional differencing). In both cases errors are modeled
assuming the occurrence of volatility. The forecast power of each model
will be compared using the criterion of the mean squared error (MSE).
The estimation of fractional term (d) will be also used to examine the
long run dependency properties of the series. The results showed that,
for all series, returns are stationary. The sugar series, however, showed
anti-persistency, while all other series showed to be long memory. The
ARFIMA models showed, in general, a better forecasting performance.